/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package me.wpf.flink;

import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010;


public class StreamingJob {

    public static void main(String[] args) throws Exception {
        // 1.获取flink运行环境
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //设置启动点检查
        env.enableCheckpointing(5000);
        env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);

        //2.设置数据源
        FlinkKafkaConsumer010<String> stringFlinkKafkaConsumer010 = new FlinkKafkaConsumer010<>(args[0], new SimpleStringSchema(), KafkaPropertiesHelper.getInstance().getProperties());
        //stringFlinkKafkaConsumer010.assignTimestampsAndWatermarks(new MessageWaterEmitter());




        /*
         * Here, you can start creating your execution plan for Flink.
         *
         * Start with getting some data from the environment, like
         * 	env.readTextFile(textPath);
         *
         * then, transform the resulting DataStream<String> using operations
         * like
         * 	.filter()
         * 	.flatMap()
         * 	.join()
         * 	.coGroup()
         *
         * and many more.
         * Have a look at the programming guide for the Java API:
         *
         * http://flink.apache.org/docs/latest/apis/streaming/index.html
         *
         */

        // execute program
        env.execute("Flink Streaming Java API Skeleton");
    }
}
